Typical intellectual engagement, Big Five personality traits, approaches to learning and cognitive ability predictors of academic performance
Background Both ability (measured by power tests) and non‐ability (measured by preference tests) individual difference measures predict academic school outcomes. These include fluid as well as crystalized intelligence, personality traits, and learning styles. This paper examines the incremental vali...
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Published in | British journal of educational psychology Vol. 79; no. 4; pp. 769 - 782 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Oxford, UK
Blackwell Publishing Ltd
01.12.2009
British Psychological Society |
Subjects | |
Online Access | Get full text |
ISSN | 0007-0998 2044-8279 |
DOI | 10.1348/978185409X412147 |
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Abstract | Background Both ability (measured by power tests) and non‐ability (measured by preference tests) individual difference measures predict academic school outcomes. These include fluid as well as crystalized intelligence, personality traits, and learning styles. This paper examines the incremental validity of five psychometric tests and the sex and age of pupils to predict their General Certificate in Secondary Education (GCSE) test results.
Aims The aim was to determine how much variance ability and non‐ability tests can account for in predicting specific GCSE exam scores.
Sample The sample comprised 212 British schoolchildren. Of these, 123 were females. Their mean age was 15.8 years (SD 0.98 years).
Method Pupils completed three self‐report tests: the Neuroticism–Extroversion–Openness‐Five‐Factor Inventory (NEO‐FFI) which measures the ‘Big Five’ personality traits, (Costa & McCrae, 1992); the Typical Intellectual Engagement Scale (Goff & Ackerman, 1992) and a measure of learning style, the Study Process Questionnaire (SPQ; Biggs, 1987). They also completed two ability tests: the Wonderlic Personnel Test (Wonderlic, 1992) a short measure of general intelligence and the General Knowledge Test (Irving, Cammock, & Lynn, 2001) a measure of crystallized intelligence. Six months later they took their (10th grade) GCSE exams comprising four ‘core’ compulsory exams as well as a number of specific elective subjects.
Results Correlational analysis suggested that intelligence was the best predictors of school results. Preference test measures accounted for relatively little variance. Regressions indicated that over 50% of the variance in school exams for English (Literature and Language) and Maths and Science combined could be accounted for by these individual difference factors.
Conclusions Data from less than an hour's worth of testing pupils could predict school exam results 6 months later. These tests could, therefore, be used to reliably inform important decisions about how pupils are taught. |
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AbstractList | Background: Both ability (measured by power tests) and non-ability (measured by preference tests) individual difference measures predict academic school outcomes. These include fluid as well as crystalized intelligence, personality traits, and learning styles. This paper examines the incremental validity of five psychometric tests and the sex and age of pupils to predict their General Certificate in Secondary Education (GCSE) test results. Aims: The aim was to determine how much variance ability and non-ability tests can account for in predicting specific GCSE exam scores. Sample: The sample comprised 212 British schoolchildren. Of these, 123 were females. Their mean age was 15.8 years (SD 0.98 years). Method: Pupils completed three self-report tests: the Neuroticism-Extroversion-Openness-Five-Factor Inventory (NEO-FFI) which measures the 'Big Five' personality traits, (Costa & McCrae, 1992); the Typical Intellectual Engagement Scale (Goff & Ackerman, 1992) and a measure of learning style, the Study Process Questionnaire (SPQ; Biggs, 1987). They also completed two ability tests: the Wonderlic Personnel Test (Wonderlic, 1992) a short measure of general intelligence and the General Knowledge Test (Irving, Cammock, & Lynn, 2001) a measure of crystallized intelligence. Six months later they took their (10th grade) GCSE exams comprising four 'core' compulsory exams as well as a number of specific elective subjects. Results: Correlational analysis suggested that intelligence was the best predictors of school results. Preference test measures accounted for relatively little variance. Regressions indicated that over 50% of the variance in school exams for English (Literature and Language) and Maths and Science combined could be accounted for by these individual difference factors. Conclusions: Data from less than an hour's worth of testing pupils could predict school exam results 6 months later. These tests could, therefore, be used to reliably inform important decisions about how pupils are taught. Adapted from the source document. Both ability (measured by power tests) and non-ability (measured by preference tests) individual difference measures predict academic school outcomes. These include fluid as well as crystalized intelligence, personality traits, and learning styles. This paper examines the incremental validity of five psychometric tests and the sex and age of pupils to predict their General Certificate in Secondary Education (GCSE) test results. The aim was to determine how much variance ability and non-ability tests can account for in predicting specific GCSE exam scores. The sample comprised 212 British schoolchildren. Of these, 123 were females. Their mean age was 15.8 years (SD 0.98 years). Pupils completed three self-report tests: the Neuroticism-Extroversion-Openness-Five-Factor Inventory (NEO-FFI) which measures the 'Big Five' personality traits, (Costa & McCrae, 1992); the Typical Intellectual Engagement Scale (Goff & Ackerman, 1992) and a measure of learning style, the Study Process Questionnaire (SPQ; Biggs, 1987). They also completed two ability tests: the Wonderlic Personnel Test (Wonderlic, 1992) a short measure of general intelligence and the General Knowledge Test (Irving, Cammock, & Lynn, 2001) a measure of crystallized intelligence. Six months later they took their (10th grade) GCSE exams comprising four 'core' compulsory exams as well as a number of specific elective subjects. Correlational analysis suggested that intelligence was the best predictors of school results. Preference test measures accounted for relatively little variance. Regressions indicated that over 50% of the variance in school exams for English (Literature and Language) and Maths and Science combined could be accounted for by these individual difference factors. Data from less than an hour's worth of testing pupils could predict school exam results 6 months later. These tests could, therefore, be used to reliably inform important decisions about how pupils are taught. Both ability (measured by power tests) and non-ability (measured by preference tests) individual difference measures predict academic school outcomes. These include fluid as well as crystalized intelligence, personality traits, and learning styles. This paper examines the incremental validity of five psychometric tests and the sex and age of pupils to predict their General Certificate in Secondary Education (GCSE) test results.BACKGROUNDBoth ability (measured by power tests) and non-ability (measured by preference tests) individual difference measures predict academic school outcomes. These include fluid as well as crystalized intelligence, personality traits, and learning styles. This paper examines the incremental validity of five psychometric tests and the sex and age of pupils to predict their General Certificate in Secondary Education (GCSE) test results.The aim was to determine how much variance ability and non-ability tests can account for in predicting specific GCSE exam scores.AIMSThe aim was to determine how much variance ability and non-ability tests can account for in predicting specific GCSE exam scores.The sample comprised 212 British schoolchildren. Of these, 123 were females. Their mean age was 15.8 years (SD 0.98 years).SAMPLEThe sample comprised 212 British schoolchildren. Of these, 123 were females. Their mean age was 15.8 years (SD 0.98 years).Pupils completed three self-report tests: the Neuroticism-Extroversion-Openness-Five-Factor Inventory (NEO-FFI) which measures the 'Big Five' personality traits, (Costa & McCrae, 1992); the Typical Intellectual Engagement Scale (Goff & Ackerman, 1992) and a measure of learning style, the Study Process Questionnaire (SPQ; Biggs, 1987). They also completed two ability tests: the Wonderlic Personnel Test (Wonderlic, 1992) a short measure of general intelligence and the General Knowledge Test (Irving, Cammock, & Lynn, 2001) a measure of crystallized intelligence. Six months later they took their (10th grade) GCSE exams comprising four 'core' compulsory exams as well as a number of specific elective subjects.METHODPupils completed three self-report tests: the Neuroticism-Extroversion-Openness-Five-Factor Inventory (NEO-FFI) which measures the 'Big Five' personality traits, (Costa & McCrae, 1992); the Typical Intellectual Engagement Scale (Goff & Ackerman, 1992) and a measure of learning style, the Study Process Questionnaire (SPQ; Biggs, 1987). They also completed two ability tests: the Wonderlic Personnel Test (Wonderlic, 1992) a short measure of general intelligence and the General Knowledge Test (Irving, Cammock, & Lynn, 2001) a measure of crystallized intelligence. Six months later they took their (10th grade) GCSE exams comprising four 'core' compulsory exams as well as a number of specific elective subjects.Correlational analysis suggested that intelligence was the best predictors of school results. Preference test measures accounted for relatively little variance. Regressions indicated that over 50% of the variance in school exams for English (Literature and Language) and Maths and Science combined could be accounted for by these individual difference factors.RESULTSCorrelational analysis suggested that intelligence was the best predictors of school results. Preference test measures accounted for relatively little variance. Regressions indicated that over 50% of the variance in school exams for English (Literature and Language) and Maths and Science combined could be accounted for by these individual difference factors.Data from less than an hour's worth of testing pupils could predict school exam results 6 months later. These tests could, therefore, be used to reliably inform important decisions about how pupils are taught.CONCLUSIONSData from less than an hour's worth of testing pupils could predict school exam results 6 months later. These tests could, therefore, be used to reliably inform important decisions about how pupils are taught. Background Both ability (measured by power tests) and non‐ability (measured by preference tests) individual difference measures predict academic school outcomes. These include fluid as well as crystalized intelligence, personality traits, and learning styles. This paper examines the incremental validity of five psychometric tests and the sex and age of pupils to predict their General Certificate in Secondary Education (GCSE) test results. Aims The aim was to determine how much variance ability and non‐ability tests can account for in predicting specific GCSE exam scores. Sample The sample comprised 212 British schoolchildren. Of these, 123 were females. Their mean age was 15.8 years (SD 0.98 years). Method Pupils completed three self‐report tests: the Neuroticism–Extroversion–Openness‐Five‐Factor Inventory (NEO‐FFI) which measures the ‘Big Five’ personality traits, (Costa & McCrae, 1992); the Typical Intellectual Engagement Scale (Goff & Ackerman, 1992) and a measure of learning style, the Study Process Questionnaire (SPQ; Biggs, 1987). They also completed two ability tests: the Wonderlic Personnel Test (Wonderlic, 1992) a short measure of general intelligence and the General Knowledge Test (Irving, Cammock, & Lynn, 2001) a measure of crystallized intelligence. Six months later they took their (10th grade) GCSE exams comprising four ‘core’ compulsory exams as well as a number of specific elective subjects. Results Correlational analysis suggested that intelligence was the best predictors of school results. Preference test measures accounted for relatively little variance. Regressions indicated that over 50% of the variance in school exams for English (Literature and Language) and Maths and Science combined could be accounted for by these individual difference factors. Conclusions Data from less than an hour's worth of testing pupils could predict school exam results 6 months later. These tests could, therefore, be used to reliably inform important decisions about how pupils are taught. Background Both ability (measured by power tests) and non‐ability (measured by preference tests) individual difference measures predict academic school outcomes. These include fluid as well as crystalized intelligence, personality traits, and learning styles. This paper examines the incremental validity of five psychometric tests and the sex and age of pupils to predict their General Certificate in Secondary Education (GCSE) test results. Aims The aim was to determine how much variance ability and non‐ability tests can account for in predicting specific GCSE exam scores. Sample The sample comprised 212 British schoolchildren. Of these, 123 were females. Their mean age was 15.8 years ( SD 0.98 years). Method Pupils completed three self‐report tests: the Neuroticism–Extroversion–Openness‐Five‐Factor Inventory (NEO‐FFI) which measures the ‘Big Five’ personality traits, ( Costa & McCrae, 1992 ); the Typical Intellectual Engagement Scale ( Goff & Ackerman, 1992 ) and a measure of learning style, the Study Process Questionnaire (SPQ; Biggs, 1987 ). They also completed two ability tests: the Wonderlic Personnel Test ( Wonderlic, 1992 ) a short measure of general intelligence and the General Knowledge Test ( Irving, Cammock, & Lynn, 2001 ) a measure of crystallized intelligence. Six months later they took their (10th grade) GCSE exams comprising four ‘core’ compulsory exams as well as a number of specific elective subjects. Results Correlational analysis suggested that intelligence was the best predictors of school results. Preference test measures accounted for relatively little variance. Regressions indicated that over 50% of the variance in school exams for English (Literature and Language) and Maths and Science combined could be accounted for by these individual difference factors. Conclusions Data from less than an hour's worth of testing pupils could predict school exam results 6 months later. These tests could, therefore, be used to reliably inform important decisions about how pupils are taught. Both ability (measured by power tests) and non-ability (measured by preference tests) individual difference measures predict academic school outcomes. These include fluid as well as crystalized intelligence, personality traits, and learning styles. This paper examines the incremental validity of five psychometric tests and the sex and age of pupils to predict their General Certificate in Secondary Education (GCSE) test results. The aim was to determine how much variance ability and non-ability tests can account for in predicting specific GCSE exam scores. The sample comprised 212 British schoolchildren. Of these, 123 were females. Their mean age was 15.8 years (SD 0.98 years). Pupils completed three self-report tests: the Neuroticism-Extroversion-Openness-Five-Factor Inventory (NEO-FFI) which measures the 'Big Five' personality traits, (Costa & McCrae, 1992); the Typical Intellectual Engagement Scale (Goff & Ackerman, 1992) and a measure of learning style, the Study Process Questionnaire (SPQ; Biggs, 1987). They also completed two ability tests: the Wonderlic Personnel Test (Wonderlic, 1992) a short measure of general intelligence and the General Knowledge Test (Irving, Cammock, & Lynn, 2001) a measure of crystallized intelligence. Six months later they took their (10th grade) GCSE exams comprising four 'core' compulsory exams as well as a number of specific elective subjects. Correlational analysis suggested that intelligence was the best predictors of school results. Preference test measures accounted for relatively little variance. Regressions indicated that over 50% of the variance in school exams for English (Literature and Language) and Maths and Science combined could be accounted for by these individual difference factors. Data from less than an hour's worth of testing pupils could predict school exam results 6 months later. These tests could, therefore, be used to reliably inform important decisions about how pupils are taught. Background: Both ability (measured by power tests) and non-ability (measured by preference tests) individual difference measures predict academic school outcomes. These include fluid as well as crystalized intelligence, personality traits, and learning styles. This paper examines the incremental validity of five psychometric tests and the sex and age of pupils to predict their General Certificate in Secondary Education (GCSE) test results. Aims: The aim was to determine how much variance ability and non-ability tests can account for in predicting specific GCSE exam scores. Sample: The sample comprised 212 British schoolchildren. Of these, 123 were females. Their mean age was 15.8 years (SD 0.98 years). Method: Pupils completed three self-report tests: the Neuroticism-Extroversion-Openness-Five-Factor Inventory (NEO-FFI) which measures the "Big Five" personality traits, (Costa & McCrae, 1992); the Typical Intellectual Engagement Scale (Goff & Ackerman, 1992) and a measure of learning style, the Study Process Questionnaire (SPQ; Biggs, 1987). They also completed two ability tests: the Wonderlic Personnel Test (Wonderlic, 1992) a short measure of general intelligence and the General Knowledge Test (Irving, Cammock, & Lynn, 2001) a measure of crystallized intelligence. Six months later they took their (10th grade) GCSE exams comprising four "core" compulsory exams as well as a number of specific elective subjects. Results: Correlational analysis suggested that intelligence was the best predictors of school results. Preference test measures accounted for relatively little variance. Regressions indicated that over 50% of the variance in school exams for English (Literature and Language) and Maths and Science combined could be accounted for by these individual difference factors. Conclusions: Data from less than an hour's worth of testing pupils could predict school exam results 6 months later. These tests could, therefore, be used to reliably inform important decisions about how pupils are taught. |
Audience | High Schools Grade 10 |
Author | Monsen, Jeremy Ahmetoglu, Gorkan Furnham, Adrian |
Author_xml | – sequence: 1 givenname: Adrian surname: Furnham fullname: Furnham, Adrian email: a.furnham@ucl.ac.uk organization: Department of Psychology, University College London, London, UK – sequence: 2 givenname: Jeremy surname: Monsen fullname: Monsen, Jeremy organization: Department of Psychology, University College London, London, UK – sequence: 3 givenname: Gorkan surname: Ahmetoglu fullname: Ahmetoglu, Gorkan organization: Department of Psychology, University College London, London, UK |
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Keywords | Human Learning Academic achievement Acquisition process Big Five personality model Secondary education Adolescent Cognitive ability Cognition Personality Predictive factor Performance |
Language | English |
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PublicationTitle | British journal of educational psychology |
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References | McCrae, R. R., Costa, P. T. Jr. Personality trait structure as a human universal American Psychologist 52 509-516 1997. Ackerman, P. L., Bowen, K. R., Beier, M. B., Kanfer, R. Determinants of individual differences and gender differences in knowledge Journal of Educational Psychology 93 797-825 2001. Bidjerano, T., Dai, D. The relationship between the big-five model of personality and self-regulated learning strategies Learning and Individual Differences 17 69-81 2007. Chamorro-Premuzic, T., Furnham, A. Intellectual competence and the intelligent personality: A third way in differential psychology Review of General Psychology 10 251-267 2006. Biggs, J. What do inventories of students' learning processes really measure/ British Journal of Educational Psychology 3 3-19 1993. Zhang, L. F. Does the big five predict learning approach/ Personality and Individual Differences 34 1431-1446 2003. Matthews, G., Deary, I. J. Personality traits Cambridge Cambridge University Press 1998. Rolfhus, E. L., Ackerman, P. L. Self-report knowledge: At the crossroads of ability, interest, and personality Journal of Educational Psychology 88 174-188 1996. Martin, J., Montgomery, R., Saphian, D. Personality, achievement test scores and high school percentiles as predictors of academic performance across four years of coursework Journal of Research in Personality 40 424-431 2006. Ferguson, A., Patterson, F. The five factor model of personality Personality and Individual Differences 24 789-796 1998. Woo, S., Harms, P., Kuncel, N. Integrating personality and intelligence: Typical intellectual engagement and need for cognition Personality and Individual Differences 43 1635-1639 2007. Ferguson, A. A facet and factor analysis of typical intellectual engagement Social Behaviour and Personality 27 545-562 1999. Ozer, D. J., Benet-Martinez, V. Personality and the prediction of consequential outcomes Annual Review of Psychology 57 81-821 2006. Chamorro-Premuzic, T., Furnham, A. Personality predicts academic performance: Evidence from two longitudinal studies on British University students Journal of Research in Personality 37 319-338 2003a. Furnham, A., Chamorro-Premuzic, T. Personality and intelligence as predictors of statistics examination grades Personality and Individual Differences 37 1013-1022 2004. Ackerman, P. L. Domain-specific knowledge as the dark matter of adult intelligence: Gf/gc, personality and interest correlates Journal of Gerontology: Psychological Sciences and Social Services 55 69-84 2000. Arteche, A., Chamorro-Premuzic, T., Ackerman, P., Furnham, A. Typical intellectual engagement as a by product of openness, learning approaches and self-assessed intelligence Educational Psychology 29 357-367 2009. Harris, D. Factors affecting college grades: A review of the literature, 1930-1937 Psychological Bulletin 37 125-166 1940. Fox, R., McManus, I., Winder, B. The shortened study process questionnaire British Journal of Educational Psychology 71 511-530 2001. Wonderlic, E. Wonderlic Personnel Test Illinois Libertyville Press 1992. Ackerman, P. L., Goff, M. Typical intellectual engagement and personality: Reply to Rocklin (1994) Journal of Educational Psychology 86 150-153 1994. Chamorro-Premuzic, T., Furnham, A. Personality traits and academic exam performance European Journal of Personality 17 237-250 2003b. Beier, M. E., Ackerman, P. L. Current events knowledge in adults: An investigation of age, intelligence and non-ability determinants Psychology and Aging 16 615-628 2001. Rocklin, T. Relation between typical intellectual engagement and openness: Comment on Goff and Ackerman Journal of Educational Psychology 86 145-149 1994. Biggs, J. The study process questionnaire manual Hawthorn Australian Council for Educational Research 1987. Digman, J. M. Personality structure: Emergence of the five factor model Annual Review of Psychology 41 417-440 1990. Chamorro-Premuzic, T., Furnham, A., Ackerman, P. The incremental validity of the typical intellectual engagement scale as predictor of different academic performance measures Journal of Personality Assessment 87 261-264 2006. O'Connor, M., Paunonen, S. Big five personality predictors of post-secondary academic performance Personality and Individual Differences 43 971-990 2007. Chamorro-Premuzic, T., Furnham, A. Personality and intellectual competence Mahwah, NJ Erlbaum 2005. Farsides, T., Woodfield, R. Individual and gender differences in good and first class undergraduate degree performance British Journal of Psychology 98 467-483 2006. Ackerman, P. L., Rolfhus, E. L. The locus of adult intelligence: Knowledge, abilities, and non-ability traits Psychology and Aging 14 314-330 1999. Deary, I., Strand, S., Smith, P., Fernandes, C. Intelligence and educational achievement Intelligence 35 13-21 2007. Furnham, A., Swami, V., Aertche, A., Chamorro-Premuzic, T. Cognitive ability, learning approaches and personality correlates of general knowledge Educational Psychology 28 427-437 2008. Furnham, A., Chamorro-Premuzic, T., Moutafi, J. Personality and intelligence: gender, the Big Five, self-estimated and psychometric intelligence International Journal of Selection and Assessment 13 11-24 2005. Cronbach, L. J. Essentials of psychological testing New York Halpern 1949. Ackerman, P. L., Kanfer, R., Goff, M. Cognitive and noncognitive determinants and consequences of complex skill acquisition Journal of Experimental Psychology: Applied 1 270-304 1995. Rolfhus, E. L., Ackerman, P. L. Assessing individual differences in knowledge: Knowledge structures and traits Journal of Educational Psychology 91 511-526 1999. Diseth, A. Personality and approaches to learning as predictors of academic achievement European Journal of Personality 17 143-155 2003. Chamorro-Premuzic, T., Furnham, A. A possible model to understand the personality-intelligence interface British Journal of Psychology 95 249-264 2004. Furnham, A., Monsen, J. Personality traits and intelligence predict academic school grades Learning and Individual Differences 19 28-33 2009. Costa, P. T. Jr., McCrae, R. R. Revised NEO personality inventory (NEO-PI-R) and NEO five-factor inventory (NEO-FFI): Professional manual Odessa, FL Psychological Assessment Resources 1992. Wolf, M., Ackerman, P. Extraversion and intelligence: A meta-analytic investigation Personality and Individual Differences 38 531-542 2005. Irving, P., Cammock, T., Lynn, R. Some evidence for the existence of a general factor of semantic memory and its components Personality and Individual Differences 30 857-871 2001. Duff, A., Boyle, E., Dunleavy, K., Ferguson, J. The relationship between personality, approach to learning and academic performance Personality and Individual Differences 36 1907-1920 2004. Kanfer, R., Ackerman, P. L., Heggestad, E. D. Motivational skills and self-regulation for learning: A trait perspective Learning and Individual Differences 8 185-209 1996. Landra, K., Pullmann, H., Allick, J. Personality and intelligence as predictors of academic achievement Personality and Individual Differences 42 441-451 2007. Thompson, R., Zamboanga, B. Academic aptitude and prior knowledge as predictors of student achievement in introduction to psychology Journal of Educational Psychology 96 778-784 2004. Cattell, R. B. Abilities: Their structure, growth, and action Boston, MA Houghton Mifflin 1971. Heaven, P., Ciarrochi, J., Vialle, W. Conscientiousness and eysenckian psychoticism as predictors of school grades Personality and Individual Differences 42 535-546 2007. Chamorro-Premuzic, T., Furnham, A., Lewis, M. Personality and approaches to learning predict preference for different teaching methods Learning and Individual Differences 17 241-250 2007. Jensen, A. R. Uses of sibling data in educational and psychological research American Educational Research Journal 17 153-170 1980. Goff, M., Ackerman, P. L. Personality-intelligence relations: Assessment of typical intellectual engagement Journal of Educational Psychology 84 537-553 1992. 2001; 93 2003a; 37 2003; 17 1971 1993; 3 2007; 35 1990; 41 2003b; 17 2001 2000 1997; 52 2004; 36 2000; 55 2004; 37 1999; 14 2008; 28 1987 2001; 16 2009; 19 2005; 38 1949 1999; 91 1996; 8 1992; 84 2007; 17 2001; 71 2006; 57 2006; 10 2006; 98 1999; 27 1998 1995 1994 2005 1940; 37 1992 2002 1995; 1 2009; 29 1994; 86 1998; 24 2003; 34 1980; 17 2004; 96 2004; 95 2006; 40 2006; 87 2007; 42 2007; 43 2001; 30 2005; 13 1996; 88 e_1_2_8_28_1 e_1_2_8_26_1 e_1_2_8_49_1 Biggs J. (e_1_2_8_14_1) 2001 e_1_2_8_3_1 Chamorro‐Premuzic T. (e_1_2_8_20_1) 2005 Cronbach L. J. (e_1_2_8_25_1) 1949 e_1_2_8_5_1 e_1_2_8_7_1 e_1_2_8_9_1 e_1_2_8_43_1 e_1_2_8_22_1 e_1_2_8_45_1 e_1_2_8_41_1 Ackerman P. L. (e_1_2_8_2_1) 1994 e_1_2_8_17_1 e_1_2_8_19_1 e_1_2_8_36_1 e_1_2_8_15_1 e_1_2_8_38_1 e_1_2_8_57_1 Matthews G. (e_1_2_8_47_1) 1998 e_1_2_8_32_1 e_1_2_8_55_1 e_1_2_8_34_1 e_1_2_8_53_1 Cattell R. B. (e_1_2_8_16_1) 1971 e_1_2_8_51_1 Costa P. T. (e_1_2_8_24_1) 1992 e_1_2_8_30_1 e_1_2_8_29_1 e_1_2_8_46_1 e_1_2_8_27_1 e_1_2_8_48_1 Wonderlic E. (e_1_2_8_56_1) 1992 Biggs J. (e_1_2_8_13_1) 1995 Biggs J. (e_1_2_8_11_1) 1987 e_1_2_8_4_1 e_1_2_8_6_1 e_1_2_8_8_1 e_1_2_8_21_1 e_1_2_8_42_1 e_1_2_8_23_1 e_1_2_8_44_1 e_1_2_8_40_1 e_1_2_8_18_1 e_1_2_8_39_1 e_1_2_8_35_1 e_1_2_8_37_1 e_1_2_8_58_1 e_1_2_8_10_1 e_1_2_8_31_1 e_1_2_8_12_1 e_1_2_8_33_1 e_1_2_8_54_1 Ozer D. J. (e_1_2_8_50_1) 2006; 57 e_1_2_8_52_1 |
References_xml | – reference: Arteche, A., Chamorro-Premuzic, T., Ackerman, P., Furnham, A. Typical intellectual engagement as a by product of openness, learning approaches and self-assessed intelligence Educational Psychology 29 357-367 2009. – reference: Rolfhus, E. L., Ackerman, P. L. Self-report knowledge: At the crossroads of ability, interest, and personality Journal of Educational Psychology 88 174-188 1996. – reference: Furnham, A., Monsen, J. Personality traits and intelligence predict academic school grades Learning and Individual Differences 19 28-33 2009. – reference: Irving, P., Cammock, T., Lynn, R. Some evidence for the existence of a general factor of semantic memory and its components Personality and Individual Differences 30 857-871 2001. – reference: Cattell, R. B. Abilities: Their structure, growth, and action Boston, MA Houghton Mifflin 1971. – reference: Digman, J. M. Personality structure: Emergence of the five factor model Annual Review of Psychology 41 417-440 1990. – reference: Chamorro-Premuzic, T., Furnham, A., Lewis, M. Personality and approaches to learning predict preference for different teaching methods Learning and Individual Differences 17 241-250 2007. – reference: Bidjerano, T., Dai, D. The relationship between the big-five model of personality and self-regulated learning strategies Learning and Individual Differences 17 69-81 2007. – reference: Cronbach, L. J. Essentials of psychological testing New York Halpern 1949. – reference: Duff, A., Boyle, E., Dunleavy, K., Ferguson, J. The relationship between personality, approach to learning and academic performance Personality and Individual Differences 36 1907-1920 2004. – reference: Ferguson, A. A facet and factor analysis of typical intellectual engagement Social Behaviour and Personality 27 545-562 1999. – reference: Jensen, A. R. Uses of sibling data in educational and psychological research American Educational Research Journal 17 153-170 1980. – reference: Deary, I., Strand, S., Smith, P., Fernandes, C. Intelligence and educational achievement Intelligence 35 13-21 2007. – reference: Beier, M. E., Ackerman, P. L. Current events knowledge in adults: An investigation of age, intelligence and non-ability determinants Psychology and Aging 16 615-628 2001. – reference: Kanfer, R., Ackerman, P. L., Heggestad, E. D. Motivational skills and self-regulation for learning: A trait perspective Learning and Individual Differences 8 185-209 1996. – reference: Landra, K., Pullmann, H., Allick, J. Personality and intelligence as predictors of academic achievement Personality and Individual Differences 42 441-451 2007. – reference: Wonderlic, E. Wonderlic Personnel Test Illinois Libertyville Press 1992. – reference: Biggs, J. What do inventories of students' learning processes really measure/ British Journal of Educational Psychology 3 3-19 1993. – reference: Chamorro-Premuzic, T., Furnham, A. Personality and intellectual competence Mahwah, NJ Erlbaum 2005. – reference: Ackerman, P. L., Kanfer, R., Goff, M. Cognitive and noncognitive determinants and consequences of complex skill acquisition Journal of Experimental Psychology: Applied 1 270-304 1995. – reference: Farsides, T., Woodfield, R. Individual and gender differences in good and first class undergraduate degree performance British Journal of Psychology 98 467-483 2006. – reference: Chamorro-Premuzic, T., Furnham, A. A possible model to understand the personality-intelligence interface British Journal of Psychology 95 249-264 2004. – reference: Thompson, R., Zamboanga, B. Academic aptitude and prior knowledge as predictors of student achievement in introduction to psychology Journal of Educational Psychology 96 778-784 2004. – reference: Biggs, J. The study process questionnaire manual Hawthorn Australian Council for Educational Research 1987. – reference: Ozer, D. J., Benet-Martinez, V. Personality and the prediction of consequential outcomes Annual Review of Psychology 57 81-821 2006. – reference: Ferguson, A., Patterson, F. The five factor model of personality Personality and Individual Differences 24 789-796 1998. – reference: Ackerman, P. L., Rolfhus, E. L. The locus of adult intelligence: Knowledge, abilities, and non-ability traits Psychology and Aging 14 314-330 1999. – reference: Furnham, A., Chamorro-Premuzic, T., Moutafi, J. Personality and intelligence: gender, the Big Five, self-estimated and psychometric intelligence International Journal of Selection and Assessment 13 11-24 2005. – reference: Zhang, L. F. Does the big five predict learning approach/ Personality and Individual Differences 34 1431-1446 2003. – reference: Chamorro-Premuzic, T., Furnham, A. Intellectual competence and the intelligent personality: A third way in differential psychology Review of General Psychology 10 251-267 2006. – reference: Chamorro-Premuzic, T., Furnham, A. Personality predicts academic performance: Evidence from two longitudinal studies on British University students Journal of Research in Personality 37 319-338 2003a. – reference: Matthews, G., Deary, I. J. Personality traits Cambridge Cambridge University Press 1998. – reference: McCrae, R. R., Costa, P. T. Jr. Personality trait structure as a human universal American Psychologist 52 509-516 1997. – reference: O'Connor, M., Paunonen, S. Big five personality predictors of post-secondary academic performance Personality and Individual Differences 43 971-990 2007. – reference: Ackerman, P. L. Domain-specific knowledge as the dark matter of adult intelligence: Gf/gc, personality and interest correlates Journal of Gerontology: Psychological Sciences and Social Services 55 69-84 2000. – reference: Fox, R., McManus, I., Winder, B. The shortened study process questionnaire British Journal of Educational Psychology 71 511-530 2001. – reference: Goff, M., Ackerman, P. L. Personality-intelligence relations: Assessment of typical intellectual engagement Journal of Educational Psychology 84 537-553 1992. – reference: Chamorro-Premuzic, T., Furnham, A., Ackerman, P. The incremental validity of the typical intellectual engagement scale as predictor of different academic performance measures Journal of Personality Assessment 87 261-264 2006. – reference: Diseth, A. Personality and approaches to learning as predictors of academic achievement European Journal of Personality 17 143-155 2003. – reference: Martin, J., Montgomery, R., Saphian, D. Personality, achievement test scores and high school percentiles as predictors of academic performance across four years of coursework Journal of Research in Personality 40 424-431 2006. – reference: Rolfhus, E. L., Ackerman, P. L. Assessing individual differences in knowledge: Knowledge structures and traits Journal of Educational Psychology 91 511-526 1999. – reference: Wolf, M., Ackerman, P. Extraversion and intelligence: A meta-analytic investigation Personality and Individual Differences 38 531-542 2005. – reference: Heaven, P., Ciarrochi, J., Vialle, W. Conscientiousness and eysenckian psychoticism as predictors of school grades Personality and Individual Differences 42 535-546 2007. – reference: Harris, D. Factors affecting college grades: A review of the literature, 1930-1937 Psychological Bulletin 37 125-166 1940. – reference: Furnham, A., Chamorro-Premuzic, T. Personality and intelligence as predictors of statistics examination grades Personality and Individual Differences 37 1013-1022 2004. – reference: Rocklin, T. Relation between typical intellectual engagement and openness: Comment on Goff and Ackerman Journal of Educational Psychology 86 145-149 1994. – reference: Ackerman, P. L., Goff, M. Typical intellectual engagement and personality: Reply to Rocklin (1994) Journal of Educational Psychology 86 150-153 1994. – reference: Ackerman, P. L., Bowen, K. R., Beier, M. B., Kanfer, R. Determinants of individual differences and gender differences in knowledge Journal of Educational Psychology 93 797-825 2001. – reference: Costa, P. T. Jr., McCrae, R. R. Revised NEO personality inventory (NEO-PI-R) and NEO five-factor inventory (NEO-FFI): Professional manual Odessa, FL Psychological Assessment Resources 1992. – reference: Chamorro-Premuzic, T., Furnham, A. Personality traits and academic exam performance European Journal of Personality 17 237-250 2003b. – reference: Woo, S., Harms, P., Kuncel, N. Integrating personality and intelligence: Typical intellectual engagement and need for cognition Personality and Individual Differences 43 1635-1639 2007. – reference: Furnham, A., Swami, V., Aertche, A., Chamorro-Premuzic, T. Cognitive ability, learning approaches and personality correlates of general knowledge Educational Psychology 28 427-437 2008. – volume: 30 start-page: 857 year: 2001 end-page: 871 article-title: Some evidence for the existence of a general factor of semantic memory and its components publication-title: Personality and Individual Differences – volume: 96 start-page: 778 year: 2004 end-page: 784 article-title: Academic aptitude and prior knowledge as predictors of student achievement in introduction to psychology publication-title: Journal of Educational Psychology – year: 2005 – volume: 86 start-page: 150 year: 1994 end-page: 153 article-title: Typical intellectual engagement and personality: Reply to Rocklin (1994) publication-title: Journal of Educational Psychology – volume: 17 start-page: 143 year: 2003 end-page: 155 article-title: Personality and approaches to learning as predictors of academic achievement publication-title: European Journal of Personality – year: 2001 – volume: 29 start-page: 357 year: 2009 end-page: 367 article-title: Typical intellectual engagement as a by product of openness, learning approaches and self‐assessed intelligence publication-title: Educational Psychology – volume: 17 start-page: 241 year: 2007 end-page: 250 article-title: Personality and approaches to learning predict preference for different teaching methods publication-title: Learning and Individual Differences – year: 1971 – start-page: 147 year: 1995 end-page: 166 – volume: 84 start-page: 537 year: 1992 end-page: 553 article-title: Personality–intelligence relations: Assessment of typical intellectual engagement publication-title: Journal of Educational Psychology – year: 1998 – volume: 24 start-page: 789 year: 1998 end-page: 796 article-title: The five factor model of personality publication-title: Personality and Individual Differences – volume: 16 start-page: 615 year: 2001 end-page: 628 article-title: Current events knowledge in adults: An investigation of age, intelligence and non‐ability determinants publication-title: Psychology and Aging – volume: 93 start-page: 797 year: 2001 end-page: 825 article-title: Determinants of individual differences and gender differences in knowledge publication-title: Journal of Educational Psychology – volume: 42 start-page: 441 year: 2007 end-page: 451 article-title: Personality and intelligence as predictors of academic achievement publication-title: Personality and Individual Differences – volume: 88 start-page: 174 year: 1996 end-page: 188 article-title: Self‐report knowledge: At the crossroads of ability, interest, and personality publication-title: Journal of Educational Psychology – start-page: 1 year: 1994 end-page: 27 – volume: 55 start-page: 69 year: 2000 end-page: 84 article-title: Domain‐specific knowledge as the dark matter of adult intelligence: Gf/gc, personality and interest correlates publication-title: Journal of Gerontology: Psychological Sciences and Social Services – year: 1949 – volume: 86 start-page: 145 year: 1994 end-page: 149 article-title: Relation between typical intellectual engagement and openness: Comment on Goff and Ackerman publication-title: Journal of Educational Psychology – volume: 14 start-page: 314 year: 1999 end-page: 330 article-title: The locus of adult intelligence: Knowledge, abilities, and non‐ability traits publication-title: Psychology and Aging – volume: 42 start-page: 535 year: 2007 end-page: 546 article-title: Conscientiousness and eysenckian psychoticism as predictors of school grades publication-title: Personality and Individual Differences – volume: 28 start-page: 427 year: 2008 end-page: 437 article-title: Cognitive ability, learning approaches and personality correlates of general knowledge publication-title: Educational Psychology – volume: 38 start-page: 531 year: 2005 end-page: 542 article-title: Extraversion and intelligence: A meta‐analytic investigation publication-title: Personality and Individual Differences – volume: 8 start-page: 185 year: 1996 end-page: 209 article-title: Motivational skills and self‐regulation for learning: A trait perspective publication-title: Learning and Individual Differences – volume: 87 start-page: 261 year: 2006 end-page: 264 article-title: The incremental validity of the typical intellectual engagement scale as predictor of different academic performance measures publication-title: Journal of Personality Assessment – volume: 37 start-page: 125 year: 1940 end-page: 166 article-title: Factors affecting college grades: A review of the literature, 1930–1937 publication-title: Psychological Bulletin – volume: 40 start-page: 424 year: 2006 end-page: 431 article-title: Personality, achievement test scores and high school percentiles as predictors of academic performance across four years of coursework publication-title: Journal of Research in Personality – year: 1987 – volume: 10 start-page: 251 year: 2006 end-page: 267 article-title: Intellectual competence and the intelligent 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Snippet | Background Both ability (measured by power tests) and non‐ability (measured by preference tests) individual difference measures predict academic school... Background Both ability (measured by power tests) and non‐ability (measured by preference tests) individual difference measures predict academic school... Background: Both ability (measured by power tests) and non-ability (measured by preference tests) individual difference measures predict academic school... Both ability (measured by power tests) and non-ability (measured by preference tests) individual difference measures predict academic school outcomes. These... |
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SubjectTerms | Academic achievement Achievement Adolescent Aptitude Biological and medical sciences Character Cognitive Ability Cognitive Style Correlation Correlation analysis Educational evaluation Educational psychology Elective Courses England Female Five factor model Foreign Countries Fundamental and applied biological sciences. Psychology Grade 10 High School Students Humans Individual Differences Individuality Intelligence Intelligence Tests Learning Learning styles Male Occupational Tests Personality Personality Inventory - statistics & numerical data Personality Traits Predictor Variables Preferences Psychology. Psychoanalysis. Psychiatry Psychology. Psychophysiology Psychometrics Psychometrics - statistics & numerical data Pupil and student. Academic achievement and failure Pupils Questionnaires Reproducibility of Results Secondary Education Secondary school students Standardized Tests Study Process Questionnaire (Biggs) Test Results Testing United Kingdom Wonderlic Personnel Test |
Title | Typical intellectual engagement, Big Five personality traits, approaches to learning and cognitive ability predictors of academic performance |
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